{"id":"https://openalex.org/W4206429670","doi":"https://doi.org/10.1109/ivworkshops54471.2021.9669218","title":"Machine learning based 3D object detection for navigation in unstructured environments","display_name":"Machine learning based 3D object detection for navigation in unstructured environments","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W4206429670","doi":"https://doi.org/10.1109/ivworkshops54471.2021.9669218"},"language":"en","primary_location":{"id":"doi:10.1109/ivworkshops54471.2021.9669218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivworkshops54471.2021.9669218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006929597","display_name":"Gjorgji Nikolovski","orcid":"https://orcid.org/0000-0002-6009-8148"},"institutions":[{"id":"https://openalex.org/I99977706","display_name":"FH Aachen","ror":"https://ror.org/04tqgg260","country_code":"DE","type":"education","lineage":["https://openalex.org/I99977706"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gjorgji Nikolovski","raw_affiliation_strings":["Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany","institution_ids":["https://openalex.org/I99977706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036819498","display_name":"Michael Reke","orcid":"https://orcid.org/0000-0002-4209-8574"},"institutions":[{"id":"https://openalex.org/I99977706","display_name":"FH Aachen","ror":"https://ror.org/04tqgg260","country_code":"DE","type":"education","lineage":["https://openalex.org/I99977706"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Reke","raw_affiliation_strings":["Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany","institution_ids":["https://openalex.org/I99977706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028958651","display_name":"Ingo Elsen","orcid":null},"institutions":[{"id":"https://openalex.org/I99977706","display_name":"FH Aachen","ror":"https://ror.org/04tqgg260","country_code":"DE","type":"education","lineage":["https://openalex.org/I99977706"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ingo Elsen","raw_affiliation_strings":["Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany","institution_ids":["https://openalex.org/I99977706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079219160","display_name":"Stefan Schiffer","orcid":"https://orcid.org/0000-0003-1343-7140"},"institutions":[{"id":"https://openalex.org/I99977706","display_name":"FH Aachen","ror":"https://ror.org/04tqgg260","country_code":"DE","type":"education","lineage":["https://openalex.org/I99977706"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Schiffer","raw_affiliation_strings":["Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mobile Autonomous Systems & Cognitive Robotics Institute, FH Aachen University of Applied Sciences, Aachen, Germany","institution_ids":["https://openalex.org/I99977706"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99977706"],"apc_list":null,"apc_paid":null,"fwci":0.7763,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74588816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"236","last_page":"242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8252446055412292},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.758202850818634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6699015498161316},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6480759978294373},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6417949199676514},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6123886704444885},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5756860971450806},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5618140697479248},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.4439210295677185},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43762844800949097},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.42597365379333496},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3445267975330353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2084910273551941},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08814498782157898}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8252446055412292},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.758202850818634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6699015498161316},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6480759978294373},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6417949199676514},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6123886704444885},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5756860971450806},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5618140697479248},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4439210295677185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43762844800949097},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.42597365379333496},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3445267975330353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2084910273551941},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08814498782157898},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivworkshops54471.2021.9669218","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivworkshops54471.2021.9669218","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.47999998927116394,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2791288346","https://openalex.org/W2949708697","https://openalex.org/W2963121255","https://openalex.org/W2963675327","https://openalex.org/W2968296999","https://openalex.org/W2991216808","https://openalex.org/W3034314779","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3117590843","https://openalex.org/W3118427100","https://openalex.org/W3161284304","https://openalex.org/W6739778489","https://openalex.org/W6760782946"],"related_works":["https://openalex.org/W2949096641","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W3034745255","https://openalex.org/W4254103348","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067"],"abstract_inverted_index":{"In":[0],"this":[1,115],"paper":[2],"we":[3,118,132,142,150,165,181],"investigate":[4],"the":[5,51,59,67,77,111,159,183,192],"use":[6],"of":[7,53,69,123,137,161,170,185,194],"deep":[8,155,188],"neural":[9,26,156,189],"networks":[10,60,71,190],"for":[11,31,87,102,126,158,175],"3D":[12,195],"object":[13,32,162,196,209],"detection":[14,33,197],"in":[15,21,34,90,114,191],"uncommon,":[16],"unstructured":[17],"environments":[18],"such":[19],"as":[20,80,106],"an":[22,62,176,211],"open-pit":[23,212],"mine.":[24,213],"While":[25,82],"nets":[27],"are":[28,95],"frequently":[29],"used":[30],"regular":[35,91],"autonomous":[36,92,177],"driving":[37,41,178],"applications,":[38],"more":[39],"unusual":[40],"scenarios":[42],"aside":[43],"street":[44],"traffic":[45],"pose":[46],"additional":[47],"challenges.":[48],"For":[49,64],"one,":[50],"collection":[52],"appropriate":[54],"data":[55,125,140,145],"sets":[56],"to":[57],"train":[58,151],"is":[61],"issue.":[63],"another,":[65],"testing":[66],"performance":[68,184],"trained":[70],"often":[72],"requires":[73],"tailored":[74],"integration":[75,169],"with":[76],"particular":[78],"domain":[79,193],"well.":[81,107],"there":[83,94],"exist":[84],"different":[85,154],"solutions":[86],"these":[88,148],"problems":[89],"driving,":[93],"only":[96],"very":[97],"few":[98],"approaches":[99],"that":[100],"work":[101],"special":[103],"domains":[104],"just":[105],"We":[108],"address":[109],"both":[110],"challenges":[112],"above":[113],"work.":[116],"First,":[117],"discuss":[119],"two":[120],"possible":[121,168],"ways":[122],"acquiring":[124],"training":[127],"and":[128,141,152,202],"evaluation.":[129],"That":[130],"is,":[131],"evaluate":[133],"a":[134,167,171,199,203,207],"semi-automated":[135],"annotation":[136],"recorded":[138],"LIDAR":[139],"examine":[143],"synthetic":[144,200],"generation.":[146],"Using":[147],"datasets":[149],"test":[153],"network":[157],"task":[160],"detection.":[163],"Second,":[164],"propose":[166],"ROS2":[172],"detector":[173],"module":[174],"platform.":[179],"Finally,":[180],"present":[182],"three":[186],"state-of-the-art":[187],"on":[198],"dataset":[201],"smaller":[204],"one":[205],"containing":[206],"characteristic":[208],"from":[210]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}